World News from data (good & bad)
Significant changes vs. 10 days ago in transmission rates, ICU demand, and cases & deaths data.
Transmission rate:
Large increase in transmission rate vs. 10 days ago, that might mean a relapse, new wave, worsening outbreak.
- Countries are sorted by size of change in transmission rate.
- Includes only countries that were previously active (more than 100 estimated new cases).
- "Large increase" = at least +2% change.
Large decrease in transmission rate vs. 10 days ago, that might mean a slowing down / effective control measures.
- Countries are sorted by size of change in transmission rate.
- Includes only countries that were previously active (more than 100 estimated new cases).
- "Large decrease" = at least -2% change.
Large increases in need for ICU beds per 100k population vs. 10 days ago.
- Only countries for which the ICU need increased by more than 0.5 (per 100k).
Large decreases in need for ICU beds per 100k population vs. 10 days ago.
- Only countries for which the ICU need decreased by more than 0.5 (per 100k).
Countries that have started their first significant outbreak (crossed 1000 total reported cases or 20 deaths) vs. 10 days ago.
New countries with no new cases or deaths vs. 10 days ago.
- Only considering countries that had at least 1000 estimated total cases and at least 10 total deaths and had an active outbreak previously.
New countries with no new deaths (only new cases) vs. 10 days ago.
- Only considering countries that had at least 1000 estimated total cases and at least 10 total deaths and had an active outbreak previously.
Countries that had no new cases or deaths 10 days ago or now.
- Only considering countries that had at least 1000 estimated total cases and at least 10 total deaths.
- Caveat:these countries may have stopped reporting data like Tanzania.
Countries with significantly higher recent death burden per 100k population vs. 10 days ago.
- "Significantly higher" = 100% more.
- Only considering countries that had at least 10 recent deaths in both timeframes, and death burden of at least 0.1 per 100k.
Countries with significantly lower recent death burden per 100k population vs. 10 days ago.
- "Significantly lower" = 50% less
- Only considering countries that had at least 10 recent deaths in both timeframes, and death burden of at least 0.1 per 100k.
Methodology
- I'm not an epidemiologist.
- Tranmission rates calculation:
- Case growth rate is calculated over the 5 past days.
- Confidence bounds are calculated by from the weighted standard deviation of the growth rate over the last 5 days. Countries with highly noisy transmission rates are exluded from tranmission rate change tables ("new waves", "slowing waves").
- Tranmission rate is calculated from cases growth rate by estimating the actively infected population change relative to the susceptible population.
- Recovery rate (for estimating actively infected):
- Where the rate estimated from Total Outstanding Cases is too high (on down-slopes) recovery probability if 1/20 is used (equivalent 20 days to recover).
- Total cases are estimated from the reported deaths for each country:
- Each country has different testing policy and capacity and cases are under-reported in some countries. Using an estimated IFR (fatality rate) we can estimate the number of cases some time ago by using the total deaths until today. We can than use this estimation to estimate the testing bias and multiply the current reported case numbers by that.
- IFRs for each country is estimated using the age IFRs from May 1 New York paper and UN demographic data for 2020. These IFRs can be found in
df['age_adjusted_ifr']column. Some examples: US - 0.98%, UK - 1.1%, Qatar - 0.25%, Italy - 1.4%, Japan - 1.6%. - The average fatality lag is assumed to be 8 days on average for a case to go from being confirmed positive (after incubation + testing lag) to death. This is the same figure used by "Estimating The Infected Population From Deaths".
- Testing bias: the actual lagged fatality rate is than divided by the IFR to estimate the testing bias in a country. The estimated testing bias then multiplies the reported case numbers to estimate the true case numbers (=case numbers if testing coverage was as comprehensive as in the heavily tested countries).
- ICU need is calculated and age-adjusted as follows:
- UK ICU ratio was reported as 4.4% of active reported cases.
- Using UKs ICU ratio and IFRs corrected for age demographics we can estimate each country's ICU ratio (the number of cases requiring ICU hospitalisation). For example using the IFR ratio between UK and Qatar to devide UK's 4.4% we get an ICU ratio of around 1% for Qatar which is also the ratio they report to WHO here.
- The ICU need is calculated from reported cases rather than from total estimated active cases. This is because the ICU ratio (4.4%) is based on reported cases.